System and method for counteracting unmanned aerial vehicles

ABSTRACT

A method for detecting unmanned aerial vehicles (UAV) includes detecting an unknown flying object in a monitored zone of air space. An image of the detected unknown flying object is captured. The captured image is analyzed to classify the detected unknown flying object. A determination is made, based on the analyzed image, whether the detected unknown flying object comprises a UAV. In response to determining that the detected unknown flying object comprises a UAV, one or more radio signals exchanged between the UAV and a user of the UAV are suppressed until the UAV departs from the monitored zone of air space.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims benefit of priority under 35 U.S.C. 119(a)-(d)to a Russian Application No. 2019130604 filed on Sep. 30, 2019, which isincorporated by reference herein.

FIELD OF TECHNOLOGY

The present disclosure relates to the field of combating unmanned aerialvehicles (UAV), and, more specifically, to system and method forcounteracting UAVs.

BACKGROUND

Unmanned vehicles are means of transportation outfitted with a system ofautomatic control which allow the unmanned vehicles to move withoutactive and constant human intervention. Such unmanned vehicles mayinclude, but are not limited to, unmanned ground transport (for example,an automobile), a self-propelled robot (for example, a lunar rover), andan unmanned aerial vehicle (for example, a quadcopter). The rapiddevelopment of complex unmanned (robotic) systems and devices requiresnew solutions for protection against them.

More specifically, UAVs, also known as drones, are becoming moreavailable for purchase by individuals, resulting in a huge increase intheir use by the public at large. Such UAVs represent civilian UAVs. Theseemingly safe commercial and individual (private) use of UAVS may beassociated with numerous dangers in the event of their improperoperation. Such use may present risks to both life and property.Moreover, UAVs may be used to violate the sanctity of commercial,educational, athletic, recreational and government existence. UAVs, suchas drones, may likewise be used to intrude on privacy or to carry outterrorist and criminal activities. For example, UAVs may fly intoresidential areas, carry explosives, or deliver contraband to prisonersby flying over prison grounds, for example. Therefore, there is agenuine need for an integrated system and method of detecting, tracking,identifying/classifying and deterring the UAVs, especially civilianUAVs. Examples of civilian UAVs include but are not limited to thedrones of such companies as DJI, FREEFLY, PARROT and XIAOMI.

One of the solutions to the aforementioned problem is utilization ofsystems which use radio frequency detection (radar). However, suchsolutions have insurmountable difficulties in the detection andidentification of small-sized flying objects. Due to the small size ofthe UAV (small unmanned aerial vehicle, SUAV) and their ability to flyat different altitudes and speeds, radar systems typically are notcapable of assuring the necessary level of detection of the flyingobjects and their subsequent identification.

Another conventional solution to the aforementioned problem involvessensors, such as, for example, light identification, detection andranging (LIDAR) devices. The advantage of LIDAR devices over radar isthat they provide a more accurate determination of the location and havea smaller spot size, which enables a more accurate image of the targetto be formed. Lidar is a device designed to detect, identify, anddetermine the range of objects using light reflections.

It should be noted that civilian UAVs are typically private property.The owners of the civilian UAVs might not know about the violation ofprivacy or the ban on crossing the boundaries of the air space of anobject over which the UAV is flying. Therefore, the solutions forcombating UAVs should effectively deal with the UAVs without actuallydamaging them.

Yet another criterion for consideration in designing solutions forcombating UAV is that the use of civilian UAV typically occurs in theair space over population centers (cities, urban-type settlements,villages, etc.), which likewise imposes a number of restrictions on theacceptable means of counteracting UAVs. For example, it may be necessaryfor the counteracting solutions to take into account the proximity ofvarious municipal structures and the use of various devices employingcellular networks of the municipal infrastructure.

Therefore, there is a genuine need to create a solution to effectivelycounteract any detected motion of unknown unmanned aerial vehicles inthe monitored zone of an air space.

SUMMARY

Aspects of the present disclosure address the above described problemsand shortcomings known in the art. Various aspects provide an integratedsolution for the detection, classification, recognition andcounteracting of unmanned aerial vehicles, especially civilian UAVs,without damaging them. Such integrated solution may be used ingovernment, commercial, private and public interests. One of the aspectsof the present disclosure is to provide protection for a certain zone ofthe air space around an object on which or alongside which the describedherein system has been installed, against UAVs, including in the airspace over a population center. In particular, the invention relates tosolutions for the detection and counteracting of unknown UAV in theevent of their penetrating a monitored air space. Unknown UAVs are UAVsnot having authorization to be in the monitored zone of the air space.

The disclosed system perform at least a detection of a moving and/orflying object using a primary detection module, a capturing of thedetected object using a recognition module, a classification of thedetected object based on at least one captured image using a control andclassification module, an identification of the UAV using a control andclassification module in the event that the detected object isdetermined to be a UAV. The disclosed system also takes steps tocounteract the unknown UAV using a neutralization module in the event ofno identification of the UAV. The identification of the detected UAV maybe done on the basis of “friend or foe” procedures. If the UAV is notidentified, then it may be classified as an unknown UAV.

In one aspect of the present disclosure the disclosed solution may beintegrated with an operating security system being used at the objectaround which it is required to provide protection of the air spaceagainst UAV. As used herein, the term “object” broadly refers to anykind of installations, such as houses and stadiums, and conditionallydesignated space, such as an airport.

The first technical result of the present disclosure is to broaden thearsenal of technical means for combating various UAVs, including in theair space over a population center, by probing the air space, detectingand identifying UAVs, and taking measures to remove the detected unknownUAV from the monitored zone of the air space.

The second technical result of the present disclosure is to protect theair space of a protected object, including one located in a populationcenter, against unknown UAVs by means of detection, classification andidentification of the UAV, with subsequent removal of unknown UAV fromthe air space of the protected object, if needed.

As one variant embodiment of the present invention, a method is proposedfor counteracting of unknown unmanned aerial vehicles (UAV), wherein themethod involves steps in which: a primary detection module may be usedto perform the detection of an unknown flying object in a monitored zoneof air space. The primary detection module may be used to determine thespatial coordinates of the detected unknown flying object, thedetermined spatial coordinates may be transmitted to a control andclassification module. An image of the detected unknown flying objectmay be captured using a recognition module. The control andclassification module may be used to classify the detected unknownflying object based on an analysis of at least one image obtained fromthe recognition module. In response to determining the unknown flyingobject to be a UAV using the control and classification module, theidentification of the UAV may be carried out. Upon determining the UAVas being an unknown UAV, a directional radio suppression of the controlsignal of the UAV may be performed using a neutralization module untilsuch time as the unknown UAV leaves the monitored zone of the air space.

In another aspect of the present disclosure, the protection against UAVmay be performed in the airspace of a population center.

In another aspect of the present disclosure, the identification of theunknown UAV may be done by detecting a visual marker, a GPS beacon orRFID tag indicating the ownership of the UAV. In yet another aspect,machine learning models, such as neural networks may be used during theanalysis for the classification of the detected unknown object.

In another aspect, the spatial coordinates of the location of theprimary detection module are determined prior to the search for flyingobjects in the air space.

In yet another aspect, the recognition module may include at least onevideo camera which is used for the capturing of the detected flyingobject, the capturing being done according to the spatial coordinates ofthe detected flying object.

In another aspect, the primary detection of the unknown flying objectmay be done using a LIDAR or a GPS receiver.

In yet another aspect, the recognition module may be mounted on aclewing module, enabling a displacement of the video camera by 360degrees about its axis.

In another aspect, the recognition module may include at least two videocameras, where one video camera is configured to perform generalsurveying, and the second video camera enables multiple enlargement ofthe detected flying object.

As another variant aspect of the present disclosure, a tracking of thedetected flying may be performed, during which the second video cameracloses in on the detected object in order to obtain at least one imagein which the detected flying object is represented with the requiredresolution, and at least one image is sent to the control andclassification module.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated into and constitute apart of this specification, illustrate one or more example aspects ofthe present disclosure and, together with the detailed description,serve to explain their principles and implementations.

FIG. 1 illustrates the high level architecture of a system for detectionand counteracting of UAVs with the possibility of realizing differentvariant aspects.

FIG. 2 illustrates an example of a prototype of a stationary aspect ofthe system for detection and counteracting of UAV in the air space overa population center.

FIG. 3 shows an example of the primary detection of an unknown object inthe monitored zone of an air space, in accordance with aspects of thepresent disclosure.

FIG. 4 shows an example of the capturing of an unknown object using avideo camera having a zoom functionality.

FIG. 5 shows an example of the location of the modules of a system ofprotection against UAVs at an industrial object.

FIG. 6 illustrates a flow diagram of the method of protection againstUAV in the air space over a population center.

FIG. 7 presents an example of a general-purpose computer system, apersonal computer or a server, in accordance with aspects of the presentdisclosure.

DETAILED DESCRIPTION

Aspects of the present disclosure enable solutions to the shortcomingsof the known art by presenting a system and a method for detection andcounteracting of unmanned vehicles. As used herein, the term “unmannedvehicles” broadly refers to such kinds of vehicles as groundtransportation means and aerial transportation means. Groundtransportation means, in a particular aspect, may refer to anself-propelled automobile. Air transportation means, in a particularaspect, may refer to an unmanned aerial vehicle. In a particular aspectof the disclosure, the detection and counteracting may be performed atleast with respect to UAVs. One of the advantages of the presentdisclosure is that the disclosed system may be used in populationcenters (cities), without causing damage to the infrastructure of thepopulation centers, or to the UAVs themselves. Examples of such damagemay include the damage associated with the crashing of the UAV againstvarious objects (such as buildings) and the antennas installed on them.Another example of such damage may include the damage associated withthe disruption of the functionality of various devices due to the radiofrequency suppression during the steps taken by the system to combat theUAV. In one non-limiting example such suppression may include thesuppression of a communication signal between the UAV and its operator.The disclosed system may enable its utilization in urban areas bycounteracting of the UAV using a directional radio antenna for combatingthe UAV, without disabling the onboard control system of the UAV andwithout limiting the operation of the flight mechanisms of the UAV (suchas the screws and propellers), which allows the UAV to not crash againstany object.

Another advantage of the present disclosure is the employment of a LIDARto perform at least the search for and primary detection of flyingobjects in the monitored air space. Thus, the LIDAR, by performing laserprobing of the air space, determines a cluster of points in a particularzone. The determined cluster may then be analyzed to recognize aforeign/unknown flying object.

As noted above, is the disclosed system may be designed to affordprotection against various civilian UAVs. Examples of such UAVs may bethe quadcopters created by such companies as DJI (models PHANTOM,INSPIRE, MAVIC, M600, S1000), FREEFLY (model ALTA), PARROT and XIAOMI,among many others.

Depending on the various aspects, the present disclosure may beimplemented both in a stationary and mobile form, examples of theimplementation of which are presented below.

According to aspects of the present disclosure, in order to perform itspurpose, it is desirable that the system for detection and counteractingof unmanned vehicles, and in a particular instance UAV, is installed ordeployed either directly on the object around which it is necessary toprotect the air space against UAV, or alongside that object. As usedherein, the term “object needing protection against unmanned vehicles”broadly refers to at least one of the following: some specific structure(such as a stadium, a residence), an entire infrastructure (such as anairport, a sea port, an industrial complex), a population center (suchas a city of rural type), a place for holding public events, and thelike. Likewise, different variant aspects make it possible to installthe disclosed system on an immovable object, such as the roof of abuilding, or on a movable object, such as an automobile which isoutfitted with a place to install the disclosed system. Moreover, thedisclosed system is also capable of being integrated with existingsecurity systems which are employed on objects (for example, inairports, harbors, and stadiums). After deploying the system forprotection of the air space of an object against unmanned vehicles, andin a particular instance UAV, the system may be launched in unmannedvehicle search mode, especially for UAV. The disclosed system also hasthe capability of adjusting functionality in accordance with therequirements of the location where the system is situated. Examples ofsuch requirements may include, but are not limited to, climaticconditions, a designated zone of air space and its boundaries.

In different aspects, the detection and/or neutralization of severalflying objects, including UAVs, in a monitored zone may be performedeither in sequence or simultaneously, depending on a particularconfiguration of the installed system. In addition, the disclosed systemis capable of performing the neutralization of a particular unmannedvehicle. To perform the neutralization of a particular unmanned vehicle,the disclosed system may obtain information about at least the kindand/or type of unmanned vehicle against which a particular zone of spaceneeds to be protected.

Furthermore, it will be understood that the present disclosure is notlimited to the examples shown in the figures. More specifically, thefunctionality of the disclosed system is not limited to protectionagainst UAVs, and it may also be used in a similar manner to protectagainst other kinds of unmanned vehicles.

FIG. 1 shows schematically the system for detection and counteracting ofUAV 100. In a preferred aspect, the system for detection andcounteracting of UAV 100 (hereinafter, the system of protection againstUAV 100) may include at least the following modules: a primary detectionmodule 110, a recognition module 120, a control and classificationmodule 130 and a neutralization module 140. Moreover, each module usessoftware enabling their interaction with each other and the performanceof their function.

The primary detection module 110 may be configured to detect any movingand/or flying object in the air space with subsequent determination ofthe spatial coordinates of the detected moving and/or flying object. Theprimary detection module 110 may be configured to interact at least withthe control and classification module 130. The interaction between thesemodules may include the transmittal of the data determined during theprobing of the air space and the coordinates determined for the detectedobjects. The coordinates may include at least an azimuth orientation ofthe detected unknown flying object, the altitude of the detected unknownflying object and the distance to the detected unknown flying object.

It should be noted that the capabilities of the search for and detectionof a flying object may be limited either by the technical capabilitiesof the devices used to make the primary detection module 110 in theimplementation of the system of protection against UAV 100, or by thedefined boundaries of the air space monitoring zone. Depending on theimplementation and configuration of the primary detection module 110,the detection of several flying objects may be done eithersimultaneously or sequentially (one at a time).

The primary detection module 110 may be configured to include a GPS(Global Positioning System) device and at least one of the followingdevices:

a LIDAR device delivering a laser beam capable of probing a target inthe air space;a video camera, for example, a wide-angle video camera;an audio receiver, such as a microphone;a radio frequency device (radar).

The aforementioned devices may contain software allowing them to obtainthe necessary information and interact with other modules of the systemof protection against UAV 100. Such software may be designed andconfigured based on various aspects of the system of protection againstUAV 100. It should be noted that the design and configuration of suchsoftware is outside the bounds of the present disclosure. In a preferredaspect, the primary detection module 110 may include an omnidirectionalLIDAR, which may perform a search for UAV using laser probing, incoordination with a GPS receiver. The laser probing may be carried outin a scanning sector from 0 to 360 degrees along the horizontal axis anda scanning angle from 0 to 90 degrees along the vertical axis. Thewindow along the vertical axis may attain at least 45 degrees. Dependingon various aspects, the distance to the UAV at which the UAV can bedetected by the disclosed system may vary in the range, for example,from, about 0.2 km to about 5 km. At the same time, depending on thetechnical capability of the primary detection module 110 the detectiondistance can be either increased or decreased as needed.

In yet another aspect, the primary detection module 110 may include aLIDAR, a GPS receiver, and at least one video camera. In this particularaspect, the primary detection may be achieved jointly by the LIDAR andthe video camera. It should be noted that the number of video camerasinstalled depends on the air space zone which needs to be protected, andthe necessary scanning sector (from about 0 degrees to about 360degrees). Thus, for example, 10 (ten) video cameras installed in acircle may meet the requirement of all-round visibility. Video camerasconnected to each other may communicate at least with the control andclassification module 130, which enables a searching for UAV in parallelwith the LIDAR.

In yet another aspect, the primary detection module 110 may additionallyinclude at least one audio receiver, which may also perform a search forUAV together with the control and classification module 130.

The preliminary tuning/calibration and further controlling of theprimary detection module 110 may be done by employing the control andclassification module 130. An example of calibration may include thedetermination of the spatial coordinates of the primary detection module110 relative to the other modules of the system of protection againstUAV 100, or the determination of the spatial coordinates of the primarydetection module 110 relative to the object around which it is necessaryto protect the air space. Such controlling of the primary detectionmodule 110′ may include, for example, the determination of theboundaries of the air space zone around the object needing protectionagainst flights by UAV.

The recognition module 120 may be configured to 1) capture the detectedflying object according to the data obtained from the control andclassification module 130, where the data may contain information aboutthe spatial coordinates of the detected object, 2) track (observe themovement) of the captured object, and 3) transmit information about thecaptured object to the control and classification module 130.

In an aspect, the recognition module 120 may include two video camerasinstalled on a slewing module. A first video camera (e.g., wide-anglevideo camera) may enable the tracking (video observation) of the objectin a wide angle field, and the second video camera may have a narrowerangle field. However, the second video camera may have a capability toobtain a higher resolution image of the target object using zoomfunctionality. In other words, the first video camera may be a so-calledgeneral-view camera, while the second camera may be a zoom video camera.In an aspect, the first video camera may be a video camera having a wideangle lens, and the second video camera may be a video camera containinga zoom lens with high variable focal length, making it possible tochange the scale of the image of the target object when photographedfrom the same point.

The control of the slewing module may be performed by the control andclassification module 130, which may send control commands to theslewing module to rotate the recognition module 120, for example, theinstalled video cameras in the direction of the detected flying object.The second video camera may allow to change (enlarge) the scale of theimage of the flying object both by optical magnification and/or bydigital magnification.

It should be noted that the recognition module 120 may also beconfigured to perform its function using at least one video camera. Inpart, the variant aspect may depend on the technical characteristics ofthe video cameras and the air space zone needing to be protected againstUAV. In one aspect, when the primary detection module 110 is configuredto have at least one video camera, then the recognition module 120 maycontain only a zoom video camera.

In other aspects, the recognition module 120 may consist of oradditionally include at least one of the following devices: aphotography camera and a device having infrared thermal imaging and/ornight vision function. Moreover, the recognition module 120 may alsoinclude additional devices facilitating detection, surveillance, andinformation gathering about the flying object in the air space forsubsequent analysis.

The control and classification module 130 may be further configured toprocess the data obtained from the primary detection module 110 and therecognition module 120, control the clewing module and the modules 110,120 and 140. The control and classification module 130 may be alsoconfigured to classify the detected flying object, where theclassification may include at least an analysis of the data obtainedfrom the recognition module 120. In one aspect, the control andclassification module 130 may employ a neural network, such as, forexample, an artificial neural network (ANN), to make a decision onwhether the detected object corresponds to a certain UAV type. As thedata presented for analysis, the recognition module 120 may providevarious images of the target object, depending on the device with whichsuch images are produced. Thus, for example, the video camera mayprovide at least one video frame, while the photography camera in turnmay provide a photograph. In response to determining the detected objectto be a UAV, the control and classification module 130 may send arequest to the neutralization module 140 to counteract the detected UAV.

The “neural network”, in the context of the present disclosure may beused primarily to detect objects in various images and may be used toclassify the detected objects. The images may be, for example, videoframes obtained at least from the recognition module 120. The neuralnetwork employed by the control and classification module 130 foranalysis of the video frames may be a previously trained neural networkand may also have the capability to learn on-the-fly in the course ofits operation. The neural network may be trained using a prepared listof annotated video frames representing examples of different flyingobjects of interest, including, but not limited to, UAVs of differentkinds and types operating in different climatic conditions, withdifferent foreshortening direction angles and with different backgroundillumination. In one particular aspect, a convolutional neural network(CNN) may be used by the control and classification module 130, enablingan effective recognition of objects in the analyzed images.

In an aspect, the control and classification module 130 may be a server(such as a Graphics Processing Unit “GPU” server). In a general case, aserver implementation may be understood as being a computer system, suchas the one described below in conjunction with FIG. 7. A computer systemmay be understood as being either a personal computer, such as a desktopcomputer, a notebook and a netbook, or an electronic device withwireless communications, such as a mobile telephone, a smartphone and atablet. The computer system may include various software, such as, butnot limited to: hardware, program and/or system software.

The neutralization module 140 may be configured to combat the detectedUAV. As used herein, the term “combat” generally refers to escorting theUAV out from the monitored air space. In an aspect, at least one antennamay be used by the neutralization module 140 that may be configured toenable a directional radio suppression of the control signal used tocontrol the detected UAV. The radio suppression may be performedcontinuously until the UAV leaves the monitored zone of the air space.The antenna used by the neutralization module 140 may produce the radiosuppression at least in a certain range (such as from about 20 degreesto about 25 degrees). The employed antenna(s) may be capable of jammingthe control signal at a given distance, in a particular frequency range.Thus, for example, the suppression distance of the UAV may be at least600 meters, the suppression power may be at least 100 MW, and thefrequency range in which the antenna emits may include at least thefollowing frequencies: 900 MHz, 1.2 GHz, 2.4 MHz, 5.8 GHz, L1 and L2,while the suppression of the signal of the communication channel of theUAV may be achieved using a source of white noise, without jamming theGPS receiver of the UAV.

In one aspect, the neutralization module 140 may be arranged togetherwith the recognition module 120 on the turntable of the clewing module,making it possible to change the position of the modules in accordancewith the movement of the detected flying object.

Various aspects of the present disclosure include both a stationary anda mobile implementation. Moreover, in one aspect the disclosed system ofprotection against UAV 100 can be integrated with an existing securitysystem used at the object around which the air space needs to beprotected against UAV.

When integrating the system of protection against UAV 100 with theaforementioned security system, an adaptation of the system ofprotection against UAV 100 can be done using the control andclassification module 130. During this adaptation all available devicesof the security system may be determined, such as additional videocameras. Furthermore, all devices of both systems may be attuned for ajoint operation of the detected devices and the aforementioned modulesof the system of protection against UAV 100. It should be noted that,when integrating the system of protection against UAV in a securitysystem, the control and classification module 130 may be integratedusing the control server of the security system, by installing at leastthe software including the neural network.

The working scenario of the proposed system 100 is presented in adescription of one aspect illustrated in FIG. 2.

FIG. 2 illustrates an example of a prototype of the stationary versionof the system of protection against UAV 100. Thus, the system ofprotection against UAV 100 may include at least a primary detectionmodule 210, a recognition and neutralization module 250 and a dataprocessing module 290. In turn, the primary detection module performsthe functions of the primary detection module 110 described above inconjunction with FIG. 1 and may include a LIDAR 220, a GPS receiver 230and a magnetometer (not shown in FIG. 2). The recognition andneutralization module 250 may perform the combined functions of therecognition module 120 and the neutralization module 140 described abovein conjunction with FIG. 1. The recognition and neutralization module250 may be mounted on the clewing module 240. In this example, therecognition and neutralization module 250 may be implemented as twovideo cameras: a first video camera (general-view video camera) 260 anda second video camera (video camera with zoom functionality) 265. Therecognition and neutralization module 250 may further include a group ofradio antennas 270. The group of radio antennas 270 may contain antennasfor radio suppression, where each antenna works on a certain radiofrequency. The frequencies or frequency range may be determinedaccording to the frequencies on which the UAVs operate. The dataprocessing module 290 may be configured to perform the tasks andfunctions of the control and classification module 130 (shown in FIG.1). In this example, the data processing module 290 may comprise aserver, containing a computer system capable of processing a largevolume of data, in particular graphics data. In an aspect, the dataprocessing module 290 may be incorporated in an individual housing. Suchimplementation enables sufficient mobility and ergonomic effectivenessof the system of protection against UAV 100. Communication between theprimary detection module 210, recognition and neutralization module 250and data processing module 290 may be provided at least by wiredcommunication (cable connections).

All of the indicated modules of the system of protection against UAV 100may be first installed either directly on the object around which theair space needs to be protected against UAV or alongside it. The systemof protection against UAV 100 may then be started in UAV search mode. Ifnecessary, a setting up of the system of protection against UAV 100 inaccordance with the geographical location may also be performed. Thus,for example, the setting up may involve at least one of the following:

-   -   determination of the spatial coordinates of the system of        protection against UAV 100 and its modules relative to each        other, if the modules are separated, in particular the primary        detection module 210 and the recognition and neutralization        module 290;    -   determination of the boundaries of the zone of air space in        which protection against flights of UAV will be provided;    -   setting up of the data processing used by the data processing        module 290 in its neural network classification/computations,        where the set-up may also include training the neural network in        accordance with the operating conditions of the system of        protection against UAV 100;    -   formation of the air space zone of UAV searching for the object        being protected;    -   formation of the region in the monitored zone of air space        needing to be protected against UAV;    -   generation of a location map of objects in the monitored zone of        air space using the primary detection module 210, especially        with the help of the LIDAR 220.

Thus, the system of protection against UAV 100 may be launched in searchmode for flying objects in the monitored zone of the air space.

Whenever any flying object appears in the monitored zone of air space,the primary detection module 210 may detect it using the LIDAR 220 andmay determine the coordinates of the detected flying object. The primarydetection module 210 may be further configured to send the determinedcoordinates to the data processing module 290.

In one variant aspect, the process of detection of a flying object mayinclude the following steps. The LIDAR 220 may perform a laser probingof the air space during which information is transmitted to the dataprocessing module 290. The information provided by the LIDAR 220 maycontain data on the position of various objects in the monitored zone ofthe air space in the form of points. The positions of various points maybe generated based on the reflection of the laser beams from varioussurfaces, including those of the objects. The data processing module 290may determine the presence of a flying object based on an analysis ofthe information received from the LIDAR 220. In yet another aspect, inwhich a map has been generated representing the zone of air space, theanalysis may be performed using the generated map. Next, the LIDAR 220in concert with the GPS receiver 230 may determine the spatialcoordinates of the detected flying object, and may also then track themovement of the detected flying object. The obtained data may betransmitted in real time to the data processing module 290. An exampleof the detection and image capturing of a flying object using the LIDAR220 is presented in FIG. 3, where a flying object is detected in thesquare.

Referring back to FIG. 2, next, the data processing module 290 may senda command to the clewing module, which may perform a rotation so thatthe recognition and neutralization module 250 is aimed in the directionof the unknown detected flying object. The data processing module 290may also send the coordinates of the flying object to the recognitionand neutralization module 250.

The recognition and neutralization module 250, using at least one of theaforementioned video cameras, may capture an image of the unknowndetected flying object and then may track the detected flying object'sflight movement. During the tracking of the detected flying object, therecognition and neutralization module 250 may perform a zooming on thementioned target object using the second video camera having zoomfunctionality 265. These steps may provide at least one digital videoframe with the detected object that may be used for its furtheridentification. As noted above, the second video camera 265 may be avideo camera containing a lens with high variable focal length, makingit possible to change the scale of the image of the object during itsphotographing from a single point. The second video camera 260 may be avideo camera with a wide angle lens. The second video camera 260 may beconfigured to determine and track the direction of movement of theflying object, e.g., in order not to lose the flying object from sight.It should be mentioned that capturing an image of the flying object maybe done in several ways when the mentioned two video cameras 260 and 265are present in the implementation of the recognition and neutralizationmodule 250. First, the image capturing may be done simultaneously byboth video cameras. Second, the image capturing may be done at first bythe first (general-view) video camera 260, and then a correction may beperformed by the second video camera 265. Third, the image capturing canbe done at first by the second video camera 265, which may continue totrack (monitor the movement of) the detected object. Later on, therecognition and neutralization module 250 may use the first video camera260 for guidance, if necessary. The effectiveness of each approach ofcapturing an image of the flying object may depend on the distance tothat flying object and the speed of movement of the flying object. Itshould be noted that the term “capturing an image of the object” refersherein to at least an intermediate stage in the process of processingthe information on the object between the stages of detection andtracking.

In an aspect, the second video camera 265 may at first use the middlepoint of the distance to the object in order to at least capture theflying object (for example, in the form of a point) in video frames.After capturing the first image, the necessary change in scale can bedone to magnify the flying object in the video frames. An example ofcapturing an image of an unknown flying object using the video camerahaving zoom functionality 265 is presented in FIG. 4. FIG. 4 shows thecaptured flying object after zooming operation has been performed. Itshould be noted that the use of two different video cameras within therecognition and neutralization module 250 enables a guaranteed focusingon the unknown flying object with a high degree and allows tracking ofthe unknown flying object during its movement.

In other aspects, the first video camera 260 may also generate videoframes with the captured unknown flying object and transmit thegenerated video frames to the data processing module 290.

After capturing the image, the recognition and neutralization module 250may transmit at least one video frame with the captured object to thedata processing module 290. It should be noted that in this process thescale of the image of the flying object may be adjusted to produce atleast one high-quality video frame. The need to change the scale (zoomin or zoom out) may be determined by the data processing module 290depending on the analysis of the video frames during the recognition ofthe detected flying object.

In one aspect, the data processing module 290 may perform an analysis ofthe obtained data using a neural network. The employed neural networkmay receive at least one video frame obtained from the recognition andneutralization module 250 as an input, in order to classify the unknowndetected flying object. The input data may include at least video framesreceived from at least one of the first video camera 260 and/or secondvideo camera 265, as well as information from other devices employed bythe recognition and neutralization module 250 or the primary detectionmodule 210. Such devices may include at least a LIDAR, an audioreceiver, and a radar. Using the results of the analysis performed bythe neural network, the data processing module 290 may produce adecision as to whether the unknown detected flying object conforms to atleast one type of UAVs or a specific model of UAV. If the detectedflying object is determined to be a UAV, the data processing module 290may send a signal to the recognition and neutralization module 250,indicating the need to counteract the detected UAV.

As noted above, the recognition and neutralization module 250 may alsoemploy a group of radio antennas 270. In response to receiving a signalfrom the data processing module 290, the recognition and neutralizationmodule 250 may orient the radio antennas 270 at the detected UAV and mayperform a directional radio suppression of the UAV. In particular, therecognition and neutralization module 250 may perform a suppression ofthe control signal of the detected UAV, until the UAV leaves themonitored air space. The type of radio frequency used or the desiredrange of radio frequencies for the jamming may also be received by therecognition and neutralization module 250 from the data processingmodule 290. The data processing module 290 may determine the type ofradio frequencies and the desired range based on the identified UAV. Therecognition and neutralization module 250 may effectively complete itsmission when the detected UAV is removed from the monitored zone of theair space.

In a particular aspect of the system of protection against UAV 100, uponsimultaneous detection of two or more unknown flying objects by theprimary detection module 210, a prioritization may be done using thedata processing module 290 to make a decision as to the order of theclassification of the unknown flying objects, as well as theirsubsequent neutralization, if necessary. The prioritization may beperformed based at least on a comparison of the distance to the detectedflying objects and their speed of approach.

In yet another aspect of the system of protection against UAV 100, afterdetermining an unknown flying object to be a UAV, the disclosed systemmay optionally identify the affiliation of the UAV and/or its ability tobe in the monitored zone of air space. For this, a “friend or foe”technique may be used. Thus, for example, the system of protectionagainst UAV 100 may perform an additional analysis for theidentification of the UAV. The additional analysis may be based on theability to identify on the body of the UAV visual markings, the use ofinfrared emitters, RFID (Radio Frequency IDentification) tags or GPSbeacons. Accordingly, depending on the detection of one of theaforementioned identifiers, the UAV can be identified as “friend” or“foe”. For example, if the UAV has a GPS beacon, the system ofprotection against UAV 100 may obtain the coordinates from that UAV andmay identify the UAV based on the coordinates. If it is determined thatthe UAV has permission to be in the monitored zone, no counteractingwill be performed by the system. Otherwise, if the UAV is identified asunknown, a counteracting may be performed as described above.

In other aspects, the system of protection against UAV 100 may includetwo or more primary detection modules 210 and recognition andneutralization modules 250. In this case, the system of protectionagainst UAV 100 may also enable the capturing and simultaneousneutralization of two or more detected UAVs.

In yet another aspect, the monitored zone of air space may be dividedinto sectors according to distance from the object being protected.Based on the divided sectors, the system of protection against UAV 100may determine which module performs its function. For example, theprimary detection module 210 may perform the search for flying objectsin all sectors, while the recognition and neutralization module 250 mayonly cover nearby sectors. The nearby sectors may be determined based onthe distance at which the recognition and neutralization module 250 canperform its function. The sectors and the configuration of one module oranother of the system of protection against UAV 100 may be set updepending on modules' technical capabilities and depending on the needfor protection against UAV in one sector or another of the monitoredzone of air space.

FIG. 5 shows an example of the location of the modules of a system ofprotection against UAVs at an industrial object. In this example,modules 210 and 250 are spaced apart in the monitored zone at anindustrial object. It should be noted that the separation of the modulesas well as their number depends on the industrial object itself thatneeds to be protected and on the technical capabilities of therespective modules. For example, the industrial complex shown in FIG. 5is located on a large territory. Therefore, in order to effectivelyprotect the industrial complex, it is desirable to distribute themodules. In particular, the number of modules 250 may not be limited toone and may be increased to four, for example. When placing modules 250,they can be installed at different corners of the industrial object infour directions.

FIG. 6 illustrates a flow diagram of the method of protection againstUAV in the air space over a population center. In step 310, the primarydetection module 110 performs the primary detection of a flying objectin the monitored zone of an air space. The primary detection may beperformed using at least a LIDAR 220, which may perform the search bylaser probing the air space. In this step, the LIDAR 220 may only enablea detection of a flying object, but not its recognition. Therefore, atthis point, all detected flying objects are also unknown flying objects.In response to detecting at least one flying object in the monitoredzone of air space, step 320 may begin.

In step 320, the primary detection module 110 may determine the spatialcoordinates of each detected flying object and may send the determinedspatial coordinates to the control and classification module 130. Thisspatial coordinates of a detected flying object may include at least anazimuth orientation of the detected unknown flying object, the altitudeof the detected unknown flying object and the distance to the detectedunknown flying object. The control and classification module 130 maysend the received coordinates to the recognition module 120 forcapturing an image of the flying object.

In step 330, the recognition module 120 may capture an image of thedetected flying object using at least one video camera of therecognition module 120. After the image is captured, the flying objectmay be tracked and video frames with the captured flying object may begenerated by the recognition module 120. The recognition module 120 maysend the captured image(s) to the control and classification module 130.In a preferred aspect, the image capturing may be performed using twovideo cameras, where the first video camera is a video camera withwide-angle lens 260, and the second video camera is a video camerahaving zoom functionality 265. The two video cameras enable capturing ofimages of the flying object and transmittal of video frames.

In step 340, the control and classification module 130 may be used toclassify the detected object based on an analysis of at least one videoframe from the video frames obtained with at least one video camera. Forthe classification of the detected object, the control andclassification module 130 may use a neural network in the analysis ofthe video frames. The neural network may be previously trained by a listof annotated test images, representing different flying objects atvarious foreshortenings and with various backgrounds. The neural networkmay be used to analyze each obtained video frame and may generate adecision as an output. The generated decision may contain informationabout the affiliation of a particular flying object, including UAV.Moreover, if the flying object is determined to be a UAV, the decisionmay also contain information about the type and model of UAV. In aparticular aspect, if the flying object is determined to be an unknownobject, the control and classification module 130 may either output thegenerated decision to the operator of the system of protection againstUAV and may wait for a response, or the control and classificationmodule 130 may perform an additional analysis, which may be based on ananalysis of the probabilities of the flying object belonging to aparticular type of object. Based on this additional analysis, thecontrol and classification module 130 may then generate a furtherdecision as to whether the unknown object is a UAV. In yet anotheraspect, the control and classification module 130 may request additionalvideo frames and may analyze them using the neural network until it canclassify the detected flying object. In this case, if the detectedflying object is determined to be a UAV, step 350 may be performed.

In step 350, if the object is determined to be a UAV, a directionalradio suppression for the control signal of the UAV may be performed bythe neutralization module 140 until the UAV leaves the monitored zone ofthe air space. The suppression may be achieved using a list of radioantennas, such as the radio antennas 270. After the removal of thedetected UAV from the monitored zone of the air space, the suppressionmay be halted. The system of protection against UAV 100 may continuefurther searching for flying objects.

In a particular aspect, if the control and classification module 130determines an unknown detected flying object as being a UAV, in anoptional step 345, an identification of the UAV may be carried out bythe control and classification module 130. The identification of the UAVmay include the determination of whether the UAV belongs to the UAVwhich are authorized to fly in the monitored zone of the air space. Themechanism of identification of the UAV may use, for example, “friend orfoe” identification techniques. Depending on the various aspects, visualmarkers on the body of the UAV, infrared (IR) emitters, RFID tags or GPSbeacons may be used by the control and classification module 130 for theidentification of the affiliation of the UAV. In the event that theunknown detected UAV belongs to the UAV which are authorized to fly inthe monitored zone of the air space, the system of protection againstUAV 100 may stop capturing the images and may stop tracking of that UAV,but may allow the UAV to continue its movement in the air space.Otherwise, if the UAV is not identified, step 350 may be performed.

FIG. 7 is a block diagram illustrating a computer system 20 on whichaspects of systems and methods for detection of malicious files may beimplemented in accordance with an exemplary aspect. The computer system20 may represent the system of protection against UAV 100 from FIG. 1and FIG. 2 and can be in the form of multiple computing devices, or inthe form of a single computing device, for example, a desktop computer,a notebook computer, a laptop computer, a mobile computing device, asmart phone, a tablet computer, a server, a mainframe, an embeddeddevice, and other forms of computing devices.

As shown, the computer system 20 includes a central processing unit(CPU) 21, a system memory 22, and a system bus 23 connecting the varioussystem components, including the memory associated with the centralprocessing unit 21. The system bus 23 may comprise a bus memory or busmemory controller, a peripheral bus, and a local bus that is able tointeract with any other bus architecture. Examples of the buses mayinclude PCI, ISA, PCI-Express, HyperTransport™, InfiniBand™, Serial ATA,I2C, and other suitable interconnects. The central processing unit 21(also referred to as a processor) can include a single or multiple setsof processors having single or multiple cores. The processor 21 mayexecute one or more computer-executable code implementing the techniquesof the present disclosure. The system memory 22 may be any memory forstoring data used herein and/or computer programs that are executable bythe processor 21. The system memory 22 may include volatile memory suchas a random access memory (RAM) 25 and non-volatile memory such as aread only memory (ROM) 24, flash memory, etc., or any combinationthereof. The basic input/output system (BIOS) 26 may store the basicprocedures for transfer of information between elements of the computersystem 20, such as those at the time of loading the operating systemwith the use of the ROM 24.

The computer system 20 may include one or more storage devices such asone or more removable storage devices 27, one or more non-removablestorage devices 28, or a combination thereof. The one or more removablestorage devices 27 and non-removable storage devices 28 are connected tothe system bus 23 via a storage interface 32. In an aspect, the storagedevices and the corresponding computer-readable storage media arepower-independent modules for the storage of computer instructions, datastructures, program modules, and other data of the computer system 20.The system memory 22, removable storage devices 27, and non-removablestorage devices 28 may use a variety of computer-readable storage media.Examples of computer-readable storage media include machine memory suchas cache, SRAM, DRAM, zero capacitor RAM, twin transistor RAM, eDRAM,EDO RAM, DDR RAM, EEPROM, NRAM, RRAM, SONOS, PRAM; flash memory or othermemory technology such as in solid state drives (SSDs) or flash drives;magnetic cassettes, magnetic tape, and magnetic disk storage such as inhard disk drives or floppy disks; optical storage such as in compactdisks (CD-ROM) or digital versatile disks (DVDs); and any other mediumwhich may be used to store the desired data and which can be accessed bythe computer system 20.

The system memory 22, removable storage devices 27, and non-removablestorage devices 28 of the computer system 20 may be used to store anoperating system 35, additional program applications 37, other programmodules 38, and program data 39. The computer system 20 may include aperipheral interface 46 for communicating data from input devices 40,such as a keyboard, mouse, stylus, game controller, voice input device,touch input device, or other peripheral devices, such as a printer orscanner via one or more I/O ports, such as a serial port, a parallelport, a universal serial bus (USB), or other peripheral interface. Adisplay device 47 such as one or more monitors, projectors, orintegrated display, may also be connected to the system bus 23 across anoutput interface 48, such as a video adapter. In addition to the displaydevices 47, the computer system 20 may be equipped with other peripheraloutput devices (not shown), such as loudspeakers and other audiovisualdevices.

The computer system 20 may operate in a network environment, using anetwork connection to one or more remote computers 49. The remotecomputer (or computers) 49 may be local computer workstations or serverscomprising most or all of the aforementioned elements in describing thenature of a computer system 20. Other devices may also be present in thecomputer network, such as, but not limited to, routers, networkstations, peer devices or other network nodes. The computer system 20may include one or more network interfaces 51 or network adapters forcommunicating with the remote computers 49 via one or more networks suchas a local-area computer network (LAN) 50, a wide-area computer network(WAN), an intranet, and the Internet. Examples of the network interface51 may include an Ethernet interface, a Frame Relay interface, SONETinterface, and wireless interfaces.

Aspects of the present disclosure may be a system, a method, and/or acomputer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present disclosure.

The computer readable storage medium can be a tangible device that canretain and store program code in the form of instructions or datastructures that can be accessed by a processor of a computing device,such as the computing system 20. The computer readable storage mediummay be an electronic storage device, a magnetic storage device, anoptical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination thereof. Byway of example, such computer-readable storage medium can comprise arandom access memory (RAM), a read-only memory (ROM), EEPROM, a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),flash memory, a hard disk, a portable computer diskette, a memory stick,a floppy disk, or even a mechanically encoded device such as punch-cardsor raised structures in a groove having instructions recorded thereon.As used herein, a computer readable storage medium is not to beconstrued as being transitory signals per se, such as radio waves orother freely propagating electromagnetic waves, electromagnetic wavespropagating through a waveguide or transmission media, or electricalsignals transmitted through a wire.

Computer readable program instructions described herein can bedownloaded to respective computing devices from a computer readablestorage medium or to an external computer or external storage device viaa network, for example, the Internet, a local area network, a wide areanetwork and/or a wireless network. The network may comprise coppertransmission cables, optical transmission fibers, wireless transmission,routers, firewalls, switches, gateway computers and/or edge servers. Anetwork interface in each computing device receives computer readableprogram instructions from the network and forwards the computer readableprogram instructions for storage in a computer readable storage mediumwithin the respective computing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembly instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language, and conventional procedural programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a LAN or WAN, or theconnection may be made to an external computer (for example, through theInternet). In some embodiments, electronic circuitry including, forexample, programmable logic circuitry, field-programmable gate arrays(FPGA), or programmable logic arrays (PLA) may execute the computerreadable program instructions by utilizing state information of thecomputer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present disclosure.

In various aspects, the systems and methods described in the presentdisclosure can be addressed in terms of modules. The term “module” asused herein refers to a real-world device, component, or arrangement ofcomponents implemented using hardware, such as by an applicationspecific integrated circuit (ASIC) or FPGA, for example, or as acombination of hardware and software, such as by a microprocessor systemand a set of instructions to implement the module's functionality, which(while being executed) transform the microprocessor system into aspecial-purpose device. A module may also be implemented as acombination of the two, with certain functions facilitated by hardwarealone, and other functions facilitated by a combination of hardware andsoftware. In certain implementations, at least a portion, and in somecases, all, of a module may be executed on the processor of a computersystem. Accordingly, each module may be realized in a variety ofsuitable configurations, and should not be limited to any particularimplementation exemplified herein.

In the interest of clarity, not all of the routine features of theaspects are disclosed herein. It would be appreciated that in thedevelopment of any actual implementation of the present disclosure,numerous implementation-specific decisions must be made in order toachieve the developer's specific goals, and these specific goals willvary for different implementations and different developers. It isunderstood that such a development effort might be complex andtime-consuming, but would nevertheless be a routine undertaking ofengineering for those of ordinary skill in the art, having the benefitof this disclosure.

Furthermore, it is to be understood that the phraseology or terminologyused herein is for the purpose of description and not of restriction,such that the terminology or phraseology of the present specification isto be interpreted by the skilled in the art in light of the teachingsand guidance presented herein, in combination with the knowledge ofthose skilled in the relevant art(s). Moreover, it is not intended forany term in the specification or claims to be ascribed an uncommon orspecial meaning unless explicitly set forth as such.

The various aspects disclosed herein encompass present and future knownequivalents to the known modules referred to herein by way ofillustration. Moreover, while aspects and applications have been shownand described, it would be apparent to those skilled in the art havingthe benefit of this disclosure that many more modifications thanmentioned above are possible without departing from the inventiveconcepts disclosed herein.

1. A method for protecting against unmanned aerial vehicles (UAV)s, themethod comprising: detecting a flying object in a monitored zone of airspace; determining spatial coordinates of the detected flying object;capturing an image of the detected unknown flying object based on thedetermined spatial coordinates; analyzing the captured image to classifythe detected unknown flying object; determining, based on the analyzedimage, whether the detected flying object comprises a UAV; and inresponse to determining that the detected flying object comprises a UAV,suppressing one or more radio signals exchanged between the UAV and auser of the UAV until the UAV departs from the monitored zone of airspace.
 2. The method of claim 1, wherein the image is captured using arecognition module having at least one or more cameras.
 3. The method ofclaim 2, wherein at least one camera of the one or more cameras areattached to a slewing base and wherein the slewing base is configured torotate the at least one camera by about 360 degree about camera's axis.4. The method of claim 1, further comprising tracking the detectedunknown flying object.
 5. The method of claim 1, wherein theclassification of the detected unknown flying object is performed usinga trained neural network.
 6. The method of claim 1, further comprisingidentifying the UAV, in response to determining that the detectedunknown flying object comprises a UAV.
 7. The method of claim 6, whereinidentifying the UAV further comprises detecting at least one of a visualmarker, GPS (Global Positioning System) beacon, or RFID (Radio FrequencyIDentification) tag indicating the ownership of the UAV.
 8. The methodof claim 1, wherein the detected UAV comprises a UAV not authorized tobe travelling in the monitored zone of the air space.
 9. A system forprotecting against unmanned aerial vehicles (UAV)s, the systemcomprising: a hardware processor configured to: detect a flying objectin a monitored zone of air space; determine spatial coordinates of thedetected flying object; capture an image of the detected unknown flyingobject based on the determined spatial coordinates; analyze the capturedimage to classify the detected unknown flying object; determine, basedon the analyzed image, whether the detected flying object comprises aUAV; and in response to determining that the detected flying objectcomprises a UAV, suppress one or more radio signals exchanged betweenthe UAV and a user of the UAV until the UAV departs from the monitoredzone of air space.
 10. The system of claim 9, wherein the image iscaptured using a recognition module having at least one or more cameras.11. The system of claim 10, wherein at least one camera of the one ormore cameras are attached to a slewing base and wherein the slewing baseis configured to rotate the at least one camera by about 360 degreeabout camera's axis.
 12. The system of claim 9, wherein the hardwareprocessor is further configured to track the detected unknown flyingobject.
 13. The system of claim 9, wherein the classification of thedetected unknown flying object is performed using a trained neuralnetwork.
 14. The system of claim 9, wherein the hardware processor isfurther configured to identify the UAV, in response to determining thatthe detected unknown flying object comprises a UAV.
 15. The system ofclaim 14, wherein the hardware processor configured to identify the UAVis further configured to detect at least one of a visual marker, GPS(Global Positioning System) beacon, or RFID (Radio FrequencyIDentification) tag indicating the ownership of the UAV.
 16. The systemof claim 9, wherein the detected UAV comprises a UAV not authorized tobe travelling in the monitored zone of the air space.
 17. Anon-transitory computer readable medium storing thereon computerexecutable instructions for protecting against unmanned aerial vehicles(UAV)s, including instructions for: detecting a flying object in amonitored zone of air space; determining spatial coordinates of thedetected flying object; capturing an image of the detected unknownflying object based on the determined spatial coordinates; analyzing thecaptured image to classify the detected unknown flying object;determining, based on the analyzed image, whether the detected flyingobject comprises a UAV; and in response to determining that the detectedflying object comprises a UAV, suppressing one or more radio signalsexchanged between the UAV and a user of the UAV until the UAV departsfrom the monitored zone of air space.
 18. The non-transitory computerreadable medium of claim 17, wherein the image is captured using arecognition module having at least one or more cameras.
 19. Thenon-transitory computer readable medium of claim 18, wherein at leastone camera of the one or more cameras are attached to a slewing base andwherein the slewing base is configured to rotate the at least one cameraby about 360 degree about camera's axis.
 20. The non-transitory computerreadable medium of claim 17, further including instructions for trackingthe detected unknown flying object.